The Diabetes Communicator Editorial Board: Call for Applications
Bibliographic record
Abstract
The Diabetes Communicator (DC) editorial board is seeking 2 new board members. To ensure a multidisciplinary team on the editorial board, we are seeking candidates in the professions of nursing, nutrition, pharmacy, social work and physical activity. Other professions, as related to diabetes, will be considered. Board members serve an initial 2-year term and may be reappointed for 2 additional terms of office. In addition, candidates should be existing members of the Diabetes Educator Section (DES) or agree to become members of the DES upon appointment. Board Member Responsibilities (a) Collaborate with members of the editorial team to identify themes for issues and potential topics of relevance to the readership. (b) Provide a network into the diabetes healthcare community to supply suitable author candidates for articles in DC. (c) Supply written articles for DC when required. (d) Review and approve the content of articles in DC to ensure that they are factually accurate, consistent with DES/CDA policies and relevant to the target audience. (e) Act as an associate editor on at least 1 issue per year. (f) Attend meetings and teleconferences when necessary. The board currently has 3 teleconferences and 1 annual in-person meeting at the CDA professional conference. (Due to the IDF 2015 World Diabetes Congress held in Vancouver, British Columbia, there will not be a CDA conference this year; no decision on a 2015 in-person meeting has been made.) Interested Applicants Should: • be a member in good standing with the Diabetes Educator Section of the Canadian Diabetes Association professional designation • complete the following application form, along with 2 samples of written work (preferably
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.083 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.019 | 0.010 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.022 | 0.009 |
| Insufficient payload (model declined to judge) | 0.493 | 0.432 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".